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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "<table class=\"ee-notebook-buttons\" align=\"left\">\n",
        "    <td><a target=\"_blank\"  href=\"https://github.com/giswqs/earthengine-py-notebooks/tree/master/Tutorials/GlobalSurfaceWater/3_water_class_transition.ipynb\"><img width=32px src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" /> View source on GitHub</a></td>\n",
        "    <td><a target=\"_blank\"  href=\"https://nbviewer.jupyter.org/github/giswqs/earthengine-py-notebooks/blob/master/Tutorials/GlobalSurfaceWater/3_water_class_transition.ipynb\"><img width=26px src=\"https://upload.wikimedia.org/wikipedia/commons/thumb/3/38/Jupyter_logo.svg/883px-Jupyter_logo.svg.png\" />Notebook Viewer</a></td>\n",
        "    <td><a target=\"_blank\"  href=\"https://colab.research.google.com/github/giswqs/earthengine-py-notebooks/blob/master/Tutorials/GlobalSurfaceWater/3_water_class_transition.ipynb\"><img src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" /> Run in Google Colab</a></td>\n",
        "</table>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Install Earth Engine API and geemap\n",
        "Install the [Earth Engine Python API](https://developers.google.com/earth-engine/python_install) and [geemap](https://geemap.org). The **geemap** Python package is built upon the [ipyleaflet](https://github.com/jupyter-widgets/ipyleaflet) and [folium](https://github.com/python-visualization/folium) packages and implements several methods for interacting with Earth Engine data layers, such as `Map.addLayer()`, `Map.setCenter()`, and `Map.centerObject()`.\n",
        "The following script checks if the geemap package has been installed. If not, it will install geemap, which automatically installs its [dependencies](https://github.com/giswqs/geemap#dependencies), including earthengine-api, folium, and ipyleaflet."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {},
      "source": [
        "# Installs geemap package\n",
        "import subprocess\n",
        "\n",
        "try:\n",
        "    import geemap\n",
        "except ImportError:\n",
        "    print('Installing geemap ...')\n",
        "    subprocess.check_call([\"python\", '-m', 'pip', 'install', 'geemap'])"
      ],
      "outputs": [],
      "execution_count": null
    },
    {
      "cell_type": "code",
      "metadata": {},
      "source": [
        "import ee\n",
        "import geemap"
      ],
      "outputs": [],
      "execution_count": null
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Create an interactive map \n",
        "The default basemap is `Google Maps`. [Additional basemaps](https://github.com/giswqs/geemap/blob/master/geemap/basemaps.py) can be added using the `Map.add_basemap()` function. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {},
      "source": [
        "Map = geemap.Map(center=[40,-100], zoom=4)\n",
        "Map"
      ],
      "outputs": [],
      "execution_count": null
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Add Earth Engine Python script "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {},
      "source": [
        "# Add Earth Engine dataset\n",
        "###############################\n",
        "# Asset List\n",
        "###############################\n",
        "\n",
        "gsw = ee.Image('JRC/GSW1_1/GlobalSurfaceWater')\n",
        "occurrence = gsw.select('occurrence')\n",
        "change = gsw.select(\"change_abs\")\n",
        "transition = gsw.select('transition')\n",
        "roi = ee.Geometry.Polygon(\n",
        "        [[[105.531921, 10.412183],\n",
        "          [105.652770, 10.285193],\n",
        "          [105.949401, 10.520218],\n",
        "          [105.809326, 10.666006]]])\n",
        "###############################\n",
        "# Constants\n",
        "###############################\n",
        "\n",
        "VIS_OCCURRENCE = {\n",
        "    'min': 0,\n",
        "    'max': 100,\n",
        "    'palette': ['red', 'blue']\n",
        "}\n",
        "VIS_CHANGE = {\n",
        "    'min': -50,\n",
        "    'max': 50,\n",
        "    'palette': ['red', 'black', 'limegreen']\n",
        "}\n",
        "VIS_WATER_MASK = {\n",
        "  'palette': ['white', 'black']\n",
        "}\n",
        "\n",
        "###############################\n",
        "# Helper functions\n",
        "###############################\n",
        "\n",
        "# Create a feature for a transition class that includes the area covered.\n",
        "def createFeature(transition_class_stats):\n",
        "  transition_class_stats = ee.Dictionary(transition_class_stats)\n",
        "  class_number = transition_class_stats.get('transition_class_value')\n",
        "  result = {\n",
        "      'transition_class_number': class_number,\n",
        "      'transition_class_''name': lookup_names.get(class_number),\n",
        "      'transition_class_''palette': lookup_palette.get(class_number),\n",
        "      'area_m2': transition_class_stats.get('sum')\n",
        "  }\n",
        "  return ee.Feature({}, result)   # Creates a feature without a geometry.\n",
        "\n",
        "\n",
        "# Create a JSON dictionary that defines piechart colors based on the\n",
        "# transition class palette.\n",
        "# https:#developers.google.com/chart/interactive/docs/gallery/piechart\n",
        "def createPieChartSliceDictionary(fc):\n",
        "  return ee.List(fc.aggregate_array(\"transition_class_palette\")) \\\n",
        "    .map(lambda p: {'color': p}).getInfo()\n",
        "\n",
        "\n",
        "###############################\n",
        "# Calculations\n",
        "###############################\n",
        "\n",
        "# Create a dictionary for looking up names of transition classes.\n",
        "lookup_names = ee.Dictionary.fromLists(\n",
        "    ee.List(gsw.get('transition_class_values')).map(ee.String),\n",
        "    gsw.get('transition_class_names')\n",
        ")\n",
        "# Create a dictionary for looking up colors of transition classes.\n",
        "lookup_palette = ee.Dictionary.fromLists(\n",
        "    ee.List(gsw.get('transition_class_values')).map(ee.String),\n",
        "    gsw.get('transition_class_palette')\n",
        ")\n",
        "\n",
        "# Create a water mask layer, and set the image mask so that non-water areas\n",
        "# are transparent.\n",
        "water_mask = occurrence.gt(90).mask(1)\n",
        "# # Generate a histogram object and print it to the console tab.\n",
        "# histogram = ui.Chart.image.histogram({\n",
        "#   'image': change,\n",
        "#   'region': roi,\n",
        "#   'scale': 30,\n",
        "#   'minBucketWidth': 10\n",
        "# })\n",
        "# histogram.setOptions({\n",
        "#   title: 'Histogram of surface water change intensity.'\n",
        "# })\n",
        "# print(histogram)\n",
        "\n",
        "# Summarize transition classes in a region of interest.\n",
        "area_image_with_transition_class = ee.Image.pixelArea().addBands(transition)\n",
        "reduction_results = area_image_with_transition_class.reduceRegion(**{\n",
        "  'reducer': ee.Reducer.sum().group(**{\n",
        "    'groupField': 1,\n",
        "    'groupName': 'transition_class_value',\n",
        "  }),\n",
        "  'geometry': roi,\n",
        "  'scale': 30,\n",
        "  'bestEffort': True,\n",
        "})\n",
        "print('reduction_results', reduction_results.getInfo())\n",
        "\n",
        "# roi_stats = ee.List(reduction_results.get('groups'))\n",
        "\n",
        "# transition_fc = ee.FeatureCollection(roi_stats.map(createFeature))\n",
        "# print('transition_fc', transition_fc.getInfo())\n",
        "\n",
        "# # Add a summary chart.\n",
        "# transition_summary_chart = ui.Chart.feature.byFeature({\n",
        "#     features: transition_fc,\n",
        "#     xProperty: 'transition_class_name',\n",
        "#     yProperties: ['area_m2', 'transition_class_number']\n",
        "#   }) \\\n",
        "#   .setChartType('PieChart') \\\n",
        "#   .setOptions({\n",
        "#     title: 'Summary of transition class areas',\n",
        "#     slices: createPieChartSliceDictionary(transition_fc),\n",
        "#     sliceVisibilityThreshold: 0  # Don't group small slices.\n",
        "#   })\n",
        "# print(transition_summary_chart)\n",
        "\n",
        "###############################\n",
        "# Initialize Map Location\n",
        "###############################\n",
        "\n",
        "# Uncomment one of the following statements to center the map on\n",
        "# a particular location.\n",
        "# Map.setCenter(-90.162, 29.8597, 10)   # New Orleans, USA\n",
        "# Map.setCenter(-114.9774, 31.9254, 10) # Mouth of the Colorado River, Mexico\n",
        "# Map.setCenter(-111.1871, 37.0963, 11) # Lake Powell, USA\n",
        "# Map.setCenter(149.412, -35.0789, 11)  # Lake George, Australia\n",
        "Map.setCenter(105.26, 11.2134, 9)     # Mekong River Basin, SouthEast Asia\n",
        "# Map.setCenter(90.6743, 22.7382, 10)   # Meghna River, Bangladesh\n",
        "# Map.setCenter(81.2714, 16.5079, 11)   # Godavari River Basin Irrigation Project, India\n",
        "# Map.setCenter(14.7035, 52.0985, 12)   # River Oder, Germany & Poland\n",
        "# Map.setCenter(-59.1696, -33.8111, 9)  # Buenos Aires, Argentina\n",
        "# Map.setCenter(-74.4557, -8.4289, 11)  # Ucayali River, Peru\n",
        "\n",
        "###############################\n",
        "# Map Layers\n",
        "###############################\n",
        "\n",
        "Map.addLayer(water_mask, VIS_WATER_MASK, '90% occurrence water mask', False)\n",
        "Map.addLayer(occurrence.updateMask(occurrence.divide(100)), VIS_OCCURRENCE, \"Water Occurrence (1984-2015)\", False)\n",
        "Map.addLayer(change, VIS_CHANGE, 'occurrence change intensity', False)\n",
        "Map.addLayer( transition, {}, 'Transition classes (1984-2018)')\n"
      ],
      "outputs": [],
      "execution_count": null
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Display Earth Engine data layers "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {},
      "source": [
        "Map.addLayerControl() # This line is not needed for ipyleaflet-based Map.\n",
        "Map"
      ],
      "outputs": [],
      "execution_count": null
    }
  ],
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